This function has been made defunct and replaced.

  • Use as.character.corpus() to turn a corpus into a simple named character vector.

  • Use corpus_group() instead of texts(x, groups = ...) to aggregate texts by a grouping variable.

  • Use [<- instead of texts()<- for replacing texts in a corpus object.

texts(x, groups = NULL, spacer = " ")

texts(x) <- value



a corpus


grouping variable for sampling, equal in length to the number of documents. This will be evaluated in the docvars data.frame, so that docvars may be referred to by name without quoting. This also changes previous behaviours for groups. See news(Version >= "3.0", package = "quanteda") for details.


when concatenating texts by using groups, this will be the spacing added between texts. (Default is two spaces.)


character vector of the new texts


For texts, a character vector of the texts in the corpus.

For texts <-, the corpus with the updated texts.

for texts <-, a corpus with the texts replaced by value


Get or replace the texts in a corpus, with grouping options. Works for plain character vectors too, if groups is a factor.


The groups will be used for concatenating the texts based on shared values of groups, without any specified order of aggregation.

You are strongly encouraged as a good practice of text analysis workflow not to modify the substance of the texts in a corpus. Rather, this sort of processing is better performed through downstream operations. For instance, do not lowercase the texts in a corpus, or you will never be able to recover the original case. Rather, apply tokens_tolower() after applying tokens() to a corpus, or use the option tolower = TRUE in dfm().